Online transactions are becoming a primary way to conduct business. For example, individuals and corporate entities are increasingly conducting their financial affairs using online banking tools. Organizations that offer the ability to perform transactions online often manage massive amounts of data. For example, organizations maintain data regarding the types of transactions, participants in the transactions, details about the computers being used by the participants to perform the transactions, and so on.
However, online transactions also create new and extensive opportunities for fraud. As one example, a fraudster may attempt to open numerous bank accounts with fake or stolen identity information. Fake identity information can be created with relative ease (e.g., signing up for free email addresses). Additionally, identity information is routinely stolen. Thus, even if only one fraudulent attempt succeeds, the fraud is generally still profitable due to the ease and low cost of obtaining fake or stolen identity information.
Moreover, fake and/or stolen identity information can be easily discarded. For example, if one email address is identified as having been used for fraud, the fraudster may maintain the fake identity and replace only the identified email address. Therefore, the fraudster can continue to perpetrate fraud with very little inconvenience to himself despite the email having been identified as fraudulent. Alternatively, if the identity of a fraudster is deemed fraudulent, the fraudster may use the fraudulent identity to target a different organization (e.g., financial institution) or even a different branch of the same organization.
Organizations have developed a number of strategies to detect and mitigate fraud. These fraud detection strategies attempt to detect fraudulent activity by identifying suspicious or incongruent information in the massive amounts of data that the organization maintains. This can be as difficult as locating the proverbial needle in a haystack. Moreover, the fraud detection strategies are typically utilized as insular approaches. For example, the information discovered as a result of one fraud detection strategy is not applied to other aspects of an organization (e.g., branches, departments, accounts) or the organization's other fraud detection strategies. Because the fraud detection strategies do not benefit from information identified as a result of other fraud detection strategies, the fraud detection strategies redundantly identify fraudulent activity. This redundancy wastes time and resources. Alternatively, the other fraud detection strategies may not even discover the information, thereby allowing different but related frauds to be perpetrated. Thus, the fraud detection strategies are underutilized making the fraud detection strategies less effective.